Network Pharmacology and Experimental Validation to Investigate the Antidepressant Potential of Atractylodes lancea (Thunb.) DC.

Abstract

Atractylodes lancea (Thunb.) DC. (AL) has been indicated in traditional prescriptions for the treatment of depression. However, the mechanism of action of AL in the treatment of depression is still unclear. This study aimed to investigate the antidepressant potential of AL using network pharmacology, molecular docking, and animal experiments. The active components of AL were retrieved from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), and the depression-related targets were screened through the DisGeNET database. Overlapping targets of AL and depression were selected and analyzed. Ten active compounds of AL showed anti-depressant potential, including stigmasterol, 3β-acetoxyatractylone, wogonin, β-sitosterol, selina-4(14),7(11)-dien-8-one, atractylenolide I, atractylenolide II, atractylenolide III, patchoulene, and cyperene. These compounds target 28 potential antidepressant genes/proteins. Gene Ontology (GO) enrichment analysis revealed that the potential targets might directly influence neural cells and regulate neuroinflammation and neurotransmitter-related processes. The potential Kyoto Encyclopedia Genes and Genomes (KEGG) pathways for the antidepressant effects of AL include neuroactive ligand–receptor interactions, calcium signaling pathways, dopaminergic synapse, interleukin (IL)-17 signaling pathways, and the pathways of neurodegeneration. IL-6, nitric oxide synthase 3 (NOS), solute carrier family 6 member 4 (SLC6A4), estrogen receptor (ESR1), and tumor necrosis factor (TNF) were the most important proteins in the protein–protein interaction network and these proteins showed high binding affinities with the corresponding AL compounds. AL showed an antidepressant effect in mice by decreasing immobility time in the tail suspension test and increasing the total contact number in the social interaction test. This study demonstrated the antidepressant potential of AL, which provides evidence for pursuing further studies to develop a novel antidepressant.

Conocarpus lancifolius (Combretaceae): Pharmacological Effects, LC-ESI-MS/MS Profiling and In Silico Attributes

“…Neurotransmitter receptors are chief components of the neuroactive ligand–receptor interaction pathway, which plays a pivotal role in the pathophysiology of several brain disorders. The role of the calcium signaling pathway has also been implicated in different mental conditions, and the disruption of the Ca 2+ -CaM-NO/sGC (calcium-calmodulin-nitric oxide-activated guanylyl cyclase pathway) signaling cascade could result in the neuroprotective effects [ 141 ]. In this way, CLAE may exert its anxiolytic, antidepressant and memory-enhancing effect by targeting multiple underlying mechanisms.…”

Anandamide Reuptake Inhibitor (VDM11) as a Possible Candidate for COVID-19 Associated Depression; a Combination of Network Pharmacology, Molecular Docking and In Vivo Experimental Analysis

“…Cellular components (CC), molecular functions, biological processes, and pathways were all screened for target genes. KEGG pathway bubble charts made with SRPLOT (http://bioinformatics.com.cn/, accessed on 3 December 2022) were of particular interest [17].…”

“…The stronger the association between the proteins corresponding in the network, the higher the degree in the network interaction, indicating th proteins play a vital part and are deemed to be the hub genes. Based on degre ten topmost hub genes were screened, including MAPK3 (22), TNF (20), IL (19), PPARG (18), MAPK1 (17), CNR1 (13), MTOR (13), NR3C1 (11), and IGF1 The overlapped proteins were uploaded to STRING version 11.5, and high-certainty interacting proteins data with a score >0.7 were accepted for the PPI network development (Figure 3). The stronger the association between the proteins corresponding to the node in the network, the higher the degree in the network interaction, indicating that the target proteins play a vital part and are deemed to be the hub genes.…”

“…The stronger the association between the proteins corresponding to the node in the network, the higher the degree in the network interaction, indicating that the target proteins play a vital part and are deemed to be the hub genes. Based on degree values, the ten topmost hub genes were screened, including MAPK3 (22), TNF (20), IL1B (19), IL6 (19), PPARG (18), MAPK1 (17), CNR1 (13), MTOR (13), NR3C1 (11), and IGF1R (10). The overlapped proteins were uploaded to STRING version 11.5, and high-ce interacting proteins data with a score >0.7 were accepted for the PPI network develo (Figure 3).…”

Towards Novel Potential Molecular Targets for Antidepressant and Antipsychotic Pharmacotherapies

“…In general, network pharmacology utilizes the systems biology methods to analyze biological networks (e.g., metabolic or signaling pathways, protein-protein interactions) in order to infer drug actions and interactions with various targets [199]. Multiple recent studies have revealed drug targets of phytocomponents from extracts with antidepressant effects [193,194,[200][201][202], and a similar approach has been used to search for drug targets related to the treatment of schizophrenia by known schizophrenia drugs [203]. Some studies also combine docking with (Q)SAR methods, e.g., identifying monoamine neurotransmitters reuptake inhibitors as antidepressants [204] or a selective positive allosteric modulation of α1containing GABA-A receptors [196].…”